Christian Szegedy
E19896
Christian Szegedy is a computer scientist and AI researcher known for his influential work on deep learning and convolutional neural networks, including contributions to the Inception architecture.
All labels observed (1)
| Label | Occurrences |
|---|---|
| Christian Szegedy canonical | 9 |
Statements (45)
| Predicate | Object |
|---|---|
| instanceOf |
artificial intelligence researcher
ⓘ
computer scientist ⓘ research scientist ⓘ |
| coAuthor |
Alexander Toshev
ⓘ
Andrew Rabinovich ⓘ Barret Zoph ⓘ Dragomir Anguelov ⓘ Dumitru Erhan ⓘ Ian Goodfellow ⓘ
surface form:
Ian J. Goodfellow
Jonathon Shlens ⓘ Pierre Sermanet ⓘ Rupesh Kumar Srivastava ⓘ Scott Reed ⓘ Sergey Ioffe ⓘ Terrence Cai ⓘ Vijay Vasudevan ⓘ Vincent Vanhoucke ⓘ Wei Liu ⓘ Wojciech Zaremba ⓘ Zbigniew Wojna ⓘ |
| employer | Google ⓘ |
| fieldOfWork |
adversarial machine learning
ⓘ
artificial intelligence ⓘ computer science ⓘ computer vision ⓘ convolutional neural networks ⓘ deep learning ⓘ machine learning ⓘ |
| hasCitationImpactOn | ImageNet image classification ⓘ |
| hasInfluenceOn |
industrial-scale computer vision systems
ⓘ
modern convolutional neural network design ⓘ |
| hasResearchInterest |
image classification
ⓘ
neural network architectures ⓘ object detection ⓘ optimization for deep networks ⓘ scalable deep learning ⓘ |
| knownFor |
contributions to large-scale image recognition models
ⓘ
design of Inception convolutional neural network architectures ⓘ research on adversarial examples in neural networks ⓘ |
| notableWork |
Inception architecture
ⓘ
surface form:
Going Deeper with Convolutions
Inception architecture ⓘ Inception architecture ⓘ
surface form:
Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning
Intriguing properties of neural networks ⓘ Inception architecture ⓘ
surface form:
Rethinking the Inception Architecture for Computer Vision
|
| workLocation | Google Research ⓘ |
How these facts were elicited
The pipeline generated the facts above by prompting gpt-5.1 with this entity's name + description and the instruction below.
Instruction
You are a knowledge base construction expert. Given a subject entity and a description of it, return factual statements that you know for the subject as a JSON list of dictionaries(triples), where keys must be "subject", "predicate" and "object". The number of facts may be very high, between 25 to 50 or more, for very popular subjects. For less popular subjects, the number of facts can be very low, like 5 or 10. # Requirements - If you don't know the subject at all, return an empty list. - If the subject is not a named entity, return an empty list. - Include at least one triple where predicate is "instanceOf". - Do not get too wordy. - Separate several objects into multiple triples with one object.
Input
Subject: Christian Szegedy Description of subject: Christian Szegedy is a computer scientist and AI researcher known for his influential work on deep learning and convolutional neural networks, including contributions to the Inception architecture.
Referenced by (9)
Full triples — surface form annotated when it differs from this entity's canonical label.